metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-vit-flowers
results: []
finetuned-vit-flowers
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1365
- Accuracy: 0.9653
Model description
Entrenamiento apoyado de: https://github.com/huggingface/notebooks/blob/main/examples/image_classification.ipynb
Intended uses & limitations
Proyecto final
Training and evaluation data
https://huggingface.co/datasets/DeadPixels/DPhi_Sprint_25_Flowers
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1236 | 0.99 | 36 | 0.1509 | 0.9730 |
| 0.1043 | 2.0 | 73 | 0.1235 | 0.9730 |
| 0.1077 | 2.96 | 108 | 0.1365 | 0.9653 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0